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1. 发明授权

US07903883B2 Local bi-gram model for object recognition 有权
标题翻译：用于对象识别的本地bi-gram模型
公开(公告)号：US07903883B2
公开(公告)日：2011-03-08
申请号：US11694938
申请日：2007-03-30
申请人： Charles Lawrence Zitnick, III , Xiangyang Lan , Richard S. Szeliski
发明人： Charles Lawrence Zitnick, III , Xiangyang Lan , Richard S. Szeliski
IPC分类号： G06K9/00
CPC分类号： G06K9/468 , G06K9/6296
摘要： A local bi-gram model object recognition system and method for constructing a local bi-gram model and using the model to recognize objects in a query image. In a learning phase, the local bi-gram model is constructed that represents objects found in a set of training images. The local bi-gram model is a local spatial model that only models the relationship of neighboring features without any knowledge of their global context. Object recognition is performed by finding a set of matching primitives in the query image. A tree structure of matching primitives is generated and a search is performed to find a tree structure of matching primitives that obeys the local bi-gram model. The local bi-gram model can be found using unsupervised learning. The system and method also can be used to recognize objects unsupervised that are undergoing non-rigid transformations for both object instance recognition and category recognition.
摘要翻译：一种局部双向模型对象识别系统和方法，用于构建局部双向模型，并使用该模型来识别查询图像中的对象。在学习阶段，构建了表示在一组训练图像中发现的对象的局部双语模型。当地的双语模型是一种局部空间模型，它只对相邻特征的关系进行建模，而无需了解其全局环境。通过在查询图像中找到一组匹配的基元来执行对象识别。生成匹配原语的树形结构，并执行搜索以找到符合本地双语模型的匹配原语的树结构。可以使用无监督学习找到当地的双语模型。系统和方法也可用于识别无监督的对象实例识别和类别识别正在进行非刚性转换的对象。

2. 发明申请

US20080240551A1 LOCAL BI-GRAM MODEL FOR OBJECT RECOGNITION 有权
标题翻译：用于对象识别的本地BI-GRAM模型
公开(公告)号：US20080240551A1
公开(公告)日：2008-10-02
申请号：US11694938
申请日：2007-03-30
申请人： Charles Lawrence Zitnick , Xiangyang Lan , Richard S. Szeliski
发明人： Charles Lawrence Zitnick , Xiangyang Lan , Richard S. Szeliski
IPC分类号： G06K9/62
CPC分类号： G06K9/468 , G06K9/6296
摘要： A local bi-gram model object recognition system and method for constructing a local bi-gram model and using the model to recognize objects in a query image. In a learning phase, the local bi-gram model is constructed that represents objects found in a set of training images. The local bi-gram model is a local spatial model that only models the relationship of neighboring features without any knowledge of their global context. Object recognition is performed by finding a set of matching primitives in the query image. A tree structure of matching primitives is generated and a search is performed to find a tree structure of matching primitives that obeys the local bi-gram model. The local bi-gram model can be found using unsupervised learning. The system and method also can be used to recognize objects unsupervised that are undergoing non-rigid transformations for both object instance recognition and category recognition.
摘要翻译：一种局部双向模型对象识别系统和方法，用于构建局部双向模型，并使用该模型来识别查询图像中的对象。在学习阶段，构建了表示在一组训练图像中发现的对象的局部双语模型。当地的双语模型是一种局部空间模型，它只对相邻特征的关系进行建模，而无需了解其全局环境。通过在查询图像中找到一组匹配的基元来执行对象识别。生成匹配原语的树形结构，并进行搜索以找到符合本地生成模型的匹配原语的树结构。可以使用无监督学习找到当地的双语模型。系统和方法也可用于识别无监督的对象实例识别和类别识别正在进行非刚性转换的对象。

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